Junior ML / Computer Vision Engineer
Junior ML / Computer Vision Engineer
Company: My Pet Model (http://mypetmodel.com/)
Salary: $36,000k - $42,000 annually
Start Date: As soon as possible
Duration: Contract, up to negotiation
This is a fully remote, part-time position with flexible working hours
About Us:
At My Pet Model, we believe that everyone deserves to feel confident in their clothes. Oftentimes, when we shop online, the clothes that arrive don’t meet our expectations on how it looks on our body. We believe that you are the best model for your shopping experience, and our goal is to make that happen with our AI technology.
Our patent-pending AI model is the next-generation upgrade to GenAI Virtual Try-On for online fashion retail. Our AI generates personalized images of you as the model in various poses directly on the landing and category pages, and our predictive technology thinks about what customers want to shop for next. After browsing for dress pants, our AI will begin generating images of the customer in various poses for matching blazer recommendations. By helping customers visualize how clothes will look on their own body before purchasing, we hope to reduce the number of items exchanged, returned or discarded to ultimately decrease fashion waste and environmental byproducts.
We’re starting with creating our tech for pet accessories, and scaling up to womenswear by the end of the year. If you’re interested in joining a growing company filled with passionate people who want to revolutionize the fashion industry, this is the right place for you!
Job Description:
- Research, adapt, and fine-tune diffusion-based generative models to improve output quality on domain-specific data
- Design and execute structured experiments across model architectures, conditioning strategies, and training configurations
- Establish generation quality evaluation criteria and drive iterative model improvement through systematic feedback loops
- Develop and refine individual vision components within the generation pipeline — including segmentation, pose estimation, and spatial conditioning
- Build and maintain data processing, collection, annotation, and quality assurance pipelines to support model training and evaluation
Qualifications:
- A relevant Graduate degree or equivalent is preferred, students will be considered
- Solid foundation in deep learning, with practical experience training and fine-tuning vision models.
- Hands-on experience adapting pretrained diffusion models to new domains through fine-tuning, LoRA, or similar parameter-efficient methods, across tasks like inpainting, image editing, or conditional generation
- Working knowledge of how diffusion models work under the hood: attention mechanisms, architectural choices, conditioning strategies, and inference-time optimizations such as caching and distillation
- Strong grasp of core computer vision problems, including segmentation, pose estimation, depth estimation
- Ability to reason about model failure modes, design targeted experiments to address them, and communicate findings clearly
- Comfortable working independently on GPU cloud infrastructure
- Experience building or curating vision training datasets from data collection and quality filtering to mask and keypoint annotation and defining clear quality criteria is a strong plus
How to Apply:
Please apply through this platform, or send your resume and portfolio to [email protected]. We appreciate links to your github or personal website.
My Pet Model is an equal opportunity employer. We welcome applications from candidates of all backgrounds, identities, and lived experiences. If you require accommodations during the application or interview process, please send an email to [email protected].
